Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of thi...
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MDPI AG
2021-08-01
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| author | Gaëlle Prigent Kamiar Aminian Tiago Rodrigues Jean-Marc Vesin Grégoire P. Millet Mathieu Falbriard Frédéric Meyer Anisoara Paraschiv-Ionescu |
| author_facet | Gaëlle Prigent Kamiar Aminian Tiago Rodrigues Jean-Marc Vesin Grégoire P. Millet Mathieu Falbriard Frédéric Meyer Anisoara Paraschiv-Ionescu |
| author_sort | Gaëlle Prigent |
| collection | DOAJ |
| description | Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment. |
| first_indexed | 2024-03-10T08:23:53Z |
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| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T08:23:53Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
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| spelling | doaj.art-e1fa2a8840aa4ff58e42c06120e757d82023-11-22T09:43:28ZengMDPI AGSensors1424-82202021-08-012116565110.3390/s21165651Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during RunningGaëlle Prigent0Kamiar Aminian1Tiago Rodrigues2Jean-Marc Vesin3Grégoire P. Millet4Mathieu Falbriard5Frédéric Meyer6Anisoara Paraschiv-Ionescu7Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandLaboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandLaboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandApplied Signal Processing Group, Institute of Electrical Engineering of the Swiss Federal Institute of Technology, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandInstitute of Sport Sciences, University of Lausanne, 1015 Lausanne, SwitzerlandLaboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandInstitute of Sport Sciences, University of Lausanne, 1015 Lausanne, SwitzerlandLaboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, SwitzerlandRecent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.https://www.mdpi.com/1424-8220/21/16/5651breathing rate (BR)heart rate (HR)RR intervals (RR<sub>i</sub>)respiratory sinus arrhythmia (RSA)frequency tracking |
| spellingShingle | Gaëlle Prigent Kamiar Aminian Tiago Rodrigues Jean-Marc Vesin Grégoire P. Millet Mathieu Falbriard Frédéric Meyer Anisoara Paraschiv-Ionescu Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running Sensors breathing rate (BR) heart rate (HR) RR intervals (RR<sub>i</sub>) respiratory sinus arrhythmia (RSA) frequency tracking |
| title | Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running |
| title_full | Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running |
| title_fullStr | Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running |
| title_full_unstemmed | Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running |
| title_short | Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running |
| title_sort | indirect estimation of breathing rate from heart rate monitoring system during running |
| topic | breathing rate (BR) heart rate (HR) RR intervals (RR<sub>i</sub>) respiratory sinus arrhythmia (RSA) frequency tracking |
| url | https://www.mdpi.com/1424-8220/21/16/5651 |
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